MRI LI-RADS Version 2018: Impact of and Reduction in Ancillary Features.

OBJECTIVE. The purpose of this study is to determine the impact of LI-RADS ancillary features on MRI and to ascertain whether the number of ancillary features can be reduced without compromising LI-RADS accuracy. MATERIALS AND METHODS. A total of 222 liver observations in 81 consecutive patients were identified on MRI between August 2013 and December 2018. The presence or absence of major and ancillary features was used to determine the LI-RADS category for LR-1 to LR-5 observations. Final diagnosis was established on the basis of pathologic findings or one of several composite clinical reference standards. Diagnostic accuracy was compared with and without ancillary features by use of the z test of proportions. Decision tree analysis and machine learning-based feature pruning were used to identify noncontributory ancillary features for LI-RADS categorization. Interobserver agreement with and without ancillary features was measured using the Krippendorff alpha coefficient, and comparisons were made using bootstrapping. A p < .05 was considered statistically significant. RESULTS. Application of ancillary features resulted in a change in the LI-RADS category of seven hepatocellular carcinomas (HCCs), with the category of six of seven (86%) HCCs upgraded; 51 benign observations also had a change in LI-RADS category, with the category of 33 (65%) of these observations downgraded. When ancillary features were applied, the percentage of HCCs in each LI-RADS category did not differ significantly compared with major features alone (p = .06-.49). Decision tree analysis and the machine learning model identified five ancillary features as noncontributory: corona enhancement, nodule-in-nodule, mosaic architecture, blood products in mass, and fat in a mass, more than in adjacent liver. Interobserver agreement was high with and without application of ancillary features; however, it was significantly higher without ancillary features (p < .001). CONCLUSION. Although ancillary features are an important component of LI-RADS, their impact may be small. Several ancillary features likely can be removed from LI-RADS without compromising diagnostic performance.

MRI vs. CT for the Detection of Liver Metastases in Patients With Pancreatic Carcinoma: A Comparative Diagnostic Test Accuracy Systematic Review and Meta-Analysis.

BACKGROUND: The detection of liver metastases is important for pancreatic cancer curative treatment eligibility. The data suggest that magnetic resonance imaging (MRI) is more sensitive than computed tomography (CT) for the diagnosis of pancreatic cancer liver metastases. However, MRI is not currently recommended in multiple published guidelines. PURPOSE: To perform a comparative diagnostic test accuracy systematic review and meta-analysis comparing CT and MRI for pancreatic cancer liver metastases detection. STUDY TYPE: Systematic review and meta-analysis. DATA SOURCES: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and multiple radiology society meeting archives were searched until November 2018. Comparative design studies reporting on liver CT and MRI accuracy for detection of pancreatic cancer liver metastases in the same cohort were included. FIELD STRENGTH: 1.5T or 3.0T. ASSESSMENT: Demographic, methodologic, and diagnostic test accuracy data were extracted. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. STATISTICAL TESTS: Accuracy metrics were obtained using bivariate random-effects meta-analysis. The impact of different covariates on accuracy estimates was assessed using a meta-regression model. Covariates included modality, study design, tumor characteristics, risk of bias, and imaging protocols. RESULTS: Fourteen studies including 987 patients with pancreatic cancer (205 with liver metastases) were included. Sensitivity for CT and MRI was 45% (confidence intervals [95% CI] 21-71%) and 83% (95% CI 74-88%), respectively. Specificity for CT and MRI was 94% (95% CI 84-98%) and 96% (95% CI 93-97%), respectively. The greater observed sensitivity of MRI was preserved in the meta-regression model (P = 0.01), while no difference in specificity was detected (P = 0.16). CT sensitivity was highest for triphasic and quadriphasic examinations compared to single phase or biphasic protocols (P = 0.03). Most studies were at high risk of bias. DATA CONCLUSION: MRI is more sensitive than CT for pancreatic cancer liver metastases detection, accounting for confounding variables. Consideration of this finding in clinical practice guidelines is recommended. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.

Can negligible hepatic steatosis determined by magnetic resonance imaging-proton density fat fraction obviate the need for liver biopsy in potential liver donors?

The purpose of this study is to determine whether magnetic resonance (MR)-proton density fat fraction (PDFF) estimate of negligible hepatic fat percentage (<5%) can exclude significant hepatic steatosis (≥10%) in living liver donor candidates obviating the need for liver biopsy and to perform intraindividual comparisons between MR-PDFF techniques for hepatic steatosis quantification. In an ethics-approved retrospective study, 144 liver donor candidates with magnetic resonance spectroscopy (MRS) and 6-echo Dixon magnetic resonance imaging (MRI) between 2013 and 2015 were included. A subset of 32 candidates underwent liver biopsy. Hepatic fat percentage was determined using MR-PDFF and histopathology-determined fat fraction as the reference standard. A receiver operating characteristic analysis with positive predictive value, negative predictive value (NPV), sensitivity, and specificity was performed to discriminate between clinically significant steatosis (≥10%) or not (<10%) at MRS-PDFF and MRI-PDFF thresholds of 5% and 10%. Pearson correlation and Bland-Altman analyses between MRS-PDFF and MRI-PDFF were performed for intraindividual comparison of hepatic steatosis estimation. There was significant association between MRS-PDFF and MRI-PDFF with HP-FP. High NPV of 95% (95% confidence interval [CI], 78%-99%) and 100% (95% CI, 76%-100%) as well as an area under the curve of 0.90 (95% CI, 0.79-1.0) and 0.93 (95% CI, 0.84-1.0) were obtained with a cutoff threshold of 5% MRI-PDFF and MRS-PDFF, respectively, to exclude clinically significant steatosis (≥10%). Intraindividual comparison between MRS-PDFF and MRI-PDFF showed a Pearson correlation coefficient of 0.83. Bland-Altman analysis showed a mean difference of 1% with 95% limits of agreement between -1% and 3%. MR-PDFF estimate of negligible hepatic fat percentage (<5%) has sufficient NPV for excluding clinically significant hepatic steatosis (≥10%) in living liver donor candidates obviating the need for liver biopsy. It may be sufficient to acquire only the multiecho Dixon MRI-PDFF for hepatic steatosis estimation. Liver Transplantation 24 470-477 2018 AASLD.

Liver fat quantification: Comparison of dual-echo and triple-echo chemical shift MRI to MR spectroscopy.

PURPOSE: To assess the diagnostic value of MRI using dual-echo (2PD) and triple-echo (3PD) chemical shift imaging for liver fat quantification against multi-echo T2 corrected MR spectroscopy (MRS) used as the reference standard, and examine the effect of T2(*) imaging on accuracy of MRI for fat quantification. MATERIALS AND METHODS: Patients who underwent 1.5T liver MRI that incorporated 2PD, 3PD, multi-echo T2(*) and MRS were included in this IRB approved prospective study. Regions of interest were placed in the liver to measure fat fraction (FF) with 2PD and 3PD and compared with MRS-FF. A random subset of 25 patients with a wide range of MRS-FF was analyzed with an advanced FF calculation method, to prove concordance with the 3PD. The statistical analysis included correlation stratified according to T2(*), Bland-Altman analysis, and calculation of diagnostic accuracy for detection of MRS-FF>6.25%. RESULTS: 220 MRI studies were identified in 217 patients (mean BMI 28.0±5.6). 57/217 (26.2%) patients demonstrated liver steatosis (MRS-FF>6.25%). Bland-Altman analysis revealed strong agreement between 3PD and MRS (mean±1.96 SD: -0.5%±4.6%) and weaker agreement between 2PD and MRS (4.7%±16.0%). Sensitivity of 3PD for diagnosing FF> 6.25% was higher than that of 2PD. 3PD-FF showed minor discrepancies (coefficient of variation <10%) from FF measured with the advanced method. CONCLUSION: Our large series study validates the use of 3PD chemical shift sequence for detection of liver fat in the clinical environment, even in the presence of T2(*) shortening.

The percutaneous cecostomy tube in the management of fecal incontinence in children.

PURPOSE: To retrospectively evaluate experience with percutaneous cecostomies and their long-term outcomes. MATERIALS AND METHODS: Between June 1994 and March 2009, 290 patients (mean age, 10.1 y) with fecal incontinence underwent percutaneous cecostomy tube placement and subsequent tube management. Technical success, procedural complications, and long-term follow-up until March 2012 were evaluated. RESULTS: A cecostomy was successfully placed in 284 patients (98%), and 257 of 280 patients (92%) underwent a successful exchange to a low-profile tube. A total of 1,431 routine exchanges to low-profile tubes were reviewed in 258 patients (mean, 1.6 ± 1.3 routine tube changes per 1,000 days). Eighty-five patients (29%) experienced one or more early problems after cecostomy, and 10 (3%) had major complications. In the total 463,507 tube-days, 938 late problems were noted: 917 (98%) minor and 22 (2%) major. Forty patients had the cecostomy catheter removed and 141 "graduated" to an adult health care facility. CONCLUSIONS: The percutaneous cecostomy procedure provides a safe management option for fecal incontinence in the pediatric population.

Validation of supervised automated algorithm for fast quantitative evaluation of organ motion on magnetic resonance imaging.

PURPOSE: To validate a correlation coefficient template-matching algorithm applied to the supervised automated quantification of abdominal-pelvic organ motion captured on time-resolved magnetic resonance imaging. METHODS AND MATERIALS: Magnetic resonance images of 21 patients across four anatomic sites were analyzed. Representative anatomic points of interest were chosen as surrogates for organ motion. The point of interest displacements across each image frame relative to baseline were quantified manually and through the use of a template-matching software tool, termed "Motiontrack." Automated and manually acquired displacement measures, as well as the standard deviation of intrafraction motion, were compared for each image frame and for each patient. RESULTS: Discrepancies between the automated and manual displacements of > or =2 mm were uncommon, ranging in frequency of 0-9.7% (liver and prostate, respectively). The standard deviations of intrafraction motion measured with each method correlated highly (r = 0.99). Considerable interpatient variability in organ motion was demonstrated by a wide range of standard deviations in the liver (1.4-7.5 mm), uterus (1.1-8.4 mm), and prostate gland (0.8-2.7 mm). The automated algorithm performed successfully in all patients but 1 and substantially improved efficiency compared with manual quantification techniques (5 min vs. 60-90 min). CONCLUSION: Supervised automated quantification of organ motion captured on magnetic resonance imaging using a correlation coefficient template-matching algorithm was efficient, accurate, and may play an important role in off-line adaptive approaches to intrafraction motion management.